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From ÐΞ€ρ@Ҝ (๏̯͡๏) <deepuj...@gmail.com>
Subject Re: How to speed up Spark process
Date Tue, 14 Jul 2015 04:23:03 GMT
It completed in 32 minutes. Attached is screenshots. How do i speed it up ?


On Mon, Jul 13, 2015 at 9:19 PM, ÐΞ€ρ@Ҝ (๏̯͡๏) <deepujain@gmail.com> wrote:

> Its been 30 minutes and still the partitioner has not completed yet, its
> ever.
>
> Without repartition, i see this error
> https://issues.apache.org/jira/browse/SPARK-5928
>
>
>  FetchFailed(BlockManagerId(1, imran-2.ent.cloudera.com, 55028), shuffleId=1, mapId=0,
reduceId=0, message=
> org.apache.spark.shuffle.FetchFailedException: Adjusted frame length exceeds 2147483647:
3021252889 - discarded
> 	at org.apache.spark.shuffle.hash.BlockStoreShuffleFetcher$.org$apache$spark$shuffle$hash$BlockStoreShuffleFetcher$$unpackBlock$1(BlockStoreShuffleFetcher.scala:67)
> 	at org.apache.spark.shuffle.hash.BlockStoreShuffleFetcher$$anonfun$3.apply(BlockStoreShuffleFetcher.scala:83)
> 	at org.apache.spark.shuffle.hash.BlockStoreShuffleFetcher$$anonfun$3.apply(BlockStoreShuffleFetcher.scala:83)
> 	at scala.collection.Iterator$$anon$13.hasNext(Iterator.scala:371)
> 	at org.apache.spark.util.CompletionIterator.hasNext(CompletionIterator.scala:32)
>
>
>
>
> On Mon, Jul 13, 2015 at 8:34 PM, ÐΞ€ρ@Ҝ (๏̯͡๏) <deepujain@gmail.com>
> wrote:
>
>> I have 100 MB of Avro data. and i do repartition(307) is taking forever.
>>
>> 2. val x = input.repartition(7907).map( {k1,k2,k3,k4}, {inputRecord} )
>> 3. val quantiles = x.map( {k1,k2,k3,k4},  TDigest(inputRecord).asBytes
>> ).reduceByKey() [ This was groupBy earlier ]
>> 4. x.join(quantiles).coalesce(100).writeInAvro
>>
>>
>> Attached is full Scala code.
>>
>> I have 340 Yarn node cluster with 14G Ram on each node and have input
>> data of just just 100 MB.  (Hadoop takes 2.5 hours on 1 TB dataset)
>>
>>
>> ./bin/spark-submit -v --master yarn-cluster  --jars
>> /apache/hadoop-2.4.1-2.1.3.0-2-EBAY/share/hadoop/hdfs/hadoop-hdfs-2.4.1-EBAY-2.jar,/home/dvasthimal/spark1.4/lib/spark_reporting_dep_only-1.0-SNAPSHOT.jar
>>  --num-executors 330 --driver-memory 14g --driver-java-options
>> "-XX:MaxPermSize=512M -Xmx4096M -Xms4096M -verbose:gc -XX:+PrintGCDetails
>> -XX:+PrintGCTimeStamps" --executor-memory 14g --executor-cores 1 --queue
>> hdmi-others --class com.ebay.ep.poc.spark.reporting.SparkApp
>> /home/dvasthimal/spark1.4/lib/spark_reporting-1.0-SNAPSHOT.jar
>> startDate=2015-06-20 endDate=2015-06-21
>> input=/apps/hdmi-prod/b_um/epdatasets/exptsession subcommand=ppwmasterprime
>> output=/user/dvasthimal/epdatasets/ppwmasterprime buffersize=128
>> maxbuffersize=1068 maxResultSize=200G
>>
>>
>> I see this in stdout of the task on that executor
>>
>> 15/07/13 19:58:48 WARN hdfs.BlockReaderLocal: The short-circuit local reads feature
cannot be used because libhadoop cannot be loaded.
>> 15/07/13 20:00:08 INFO collection.ExternalSorter: Thread 47 spilling in-memory map
of 2.2 GB to disk (1 time so far)
>> 15/07/13 20:01:31 INFO collection.ExternalSorter: Thread 47 spilling in-memory map
of 2.2 GB to disk (2 times so far)
>> 15/07/13 20:03:07 INFO collection.ExternalSorter: Thread 47 spilling in-memory map
of 2.2 GB to disk (3 times so far)
>> 15/07/13 20:04:32 INFO collection.ExternalSorter: Thread 47 spilling in-memory map
of 2.2 GB to disk (4 times so far)
>> 15/07/13 20:06:21 INFO collection.ExternalSorter: Thread 47 spilling in-memory map
of 2.2 GB to disk (5 times so far)
>> 15/07/13 20:08:09 INFO collection.ExternalSorter: Thread 47 spilling in-memory map
of 2.2 GB to disk (6 times so far)
>> 15/07/13 20:09:51 INFO collection.ExternalSorter: Thread 47 spilling in-memory map
of 2.2 GB to disk (7 times so far)
>>
>>
>>
>> Also attached is the thread dump
>>
>>
>> --
>> Deepak
>>
>>
>
>
> --
> Deepak
>
>


-- 
Deepak

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